Element AI for Retail
Everything startsand ends with the store.
The bar has been set very low, now more than ever, it's time for a better way.
In these uncertain times, retailers will need to both manage disruption more efficiently as well as start building transition plans to get back to the “New Normal.”
Our retail products leverage your store and network-level data, enabling localized demand sensing, effective compliance and dynamic merchandise planning for store and SKU-level profitability.
Get in touchShorten planning & optimization cycles with greater store-level awareness and accuracy.
Today, more and more time, money, and effort is spent attempting to adjust plans on shorter and shorter time horizons. Supply chains are expected to be more flexible than ever, yet retailers’ central office is still struggling to reflect the local, store-specific characteristics in these plans. As a result, plans are generic and one-size-fits-no-one, causing suboptimal assortments, store operations, and logistics.
Furthermore, retailers are increasingly looking at ways to (a) glean actual shelf-level visibility and (b) ensure compliance with these aforementioned plans. Today, no digital feedback mechanism exists between the store and the corporate office to ensure the right product is in the right place on the right shelf at the right time.
Learn moreUse cases
With inventory distortion at an all-time high, coupled with carrying less than half the on-hand inventory of 20 years ago, major disruptions force category, store, warehouse, and transportation managers to rely on manual, ad hoc expertise. Armed with insufficient data and forced to make decisions in too short a timeframe, the result is rarely optimal.
- By using the conversational interface of Element AI’s Knowledge Scout tool, operations managers can evaluate more information at once, thereby improving the quality of their decisions and allowing them to prioritize more elegantly in real time.
- Additionally, the transition out of a major disruption can cause just as many issues as the disruption itself:
- 'How do I readjust my assortment back to normalcy?'
- 'What is normalcy, post-disruption?'
- 'How do I phase in adjusted customer expectations (such as increased online & delivery orders) without sacrificing the core store operations?'
- 'Is my transition period a month? A year?'
- Using a novel application of state-of-the-art forecasting, optimization, and simulation techniques, operations managers can perform What-If analysis to explore future scenarios in order to proactively determine the transition plan.
Manual processes for measuring compliance, analyzing SKU availability and determining brand competition and performance are not only time consuming and error-prone but also limit store associates from taking up customer-facing activities.
- Accurately analyze shelf images for the validation of planograms, identification of out-of-stocks, and pricing & promo compliance to ensure a consistent customer experience.
- Provide SKU/store-level insights to both the planners and the stores, allowing them to activate changes that will have a big impact on top-line growth.
The increasing complexity and fluidity of SKUs, line reviews and the locality of demand patterns are now overburdening stores and overwhelming largely manual assortment planning and planogram-development processes. In effect, an abundance of information has turned into a significant analytical burden, rather than an abundance of insight. Stores are now managing too many complex trade-offs without the analytical tools and bandwidth needed to ensure clear, data-driven decisions.
- With an inability to provide a digital feedback loop between the store and corporate office, these plans are ultimately suboptimal, resulting in substantial changes being taken by the associates in each store. Planograms can become largely meaningless, often resulting in a mere 50% accuracy once implemented in the store.
- Through a mixture of expertise, science and art, Element AI proposes a bottom-up approach to assortment and planogram optimization that can be utilized at the store level while also capturing new insights that can be used upstream to create the optimal assortment based on each location/SKU. The goal is to reduce inventory holding costs and provide a personalized experience for customers.
Global market changes are impacting day-to-day operations for retailers around the world. Some of the factors contributing to this change include the disaggregation of marketing levers, an increase in dynamic business strategies, a growing number of SKUs and product launches and the increasingly discerning and well-informed shopper.
- Demand forecasting is critical to businesses across almost all industries. It can seem easy, because there are easy ways to build simple models. But in practice, building a demand-forecasting model that is accurate and useful is a complex challenge. Accurately predicting the flow of inventory between nodes of the supply chain is crucial to decreasing operational costs, as well as to delivering a seamless customer experience, from engagement to sale to fulfillment.
- The combination of the predictive power of forecasting and the prescriptive power of optimization is critical to enabling better business outcomes.
Helping you map it all out
Most retail enterprises know it’s not a question of whether or not to deploy AI solutions, but a matter of when and where to start.
Our cross-functional team of experts can guide you through the process of driving real business value with AI, from evaluating AI business cases and identifying unique areas of innovation that require further research, through to designing MVPs and deploying sustainable, performant AI business applications at scale.
